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Use VGG model to fight cat and dog import numpy as np import matplotlib.pyplot as plt import os import shutil,os import torch import torch.nn as nn import torchvision from torchvision import models,transforms,datasets import time import json # Determine whether there is a GPU device device = torch.device("cuda:0" if torch.cuda.is_available() ...

In this paper, MNIST data set is used for training, and the graphical method is used to show the difference between the input in CGAN and GAN, so as to help understand the operation process of CGAN 1, Principle As shown in the figure below, when we input noise z, we add an additional restriction condition, z and c to obtain the generated ...

Catalogue of series articles PyTorch Week 3 - nn.MaxPool2d, nn.AvgPool2d, nn.Linear, active layer PyTorch Week 3 - convolution PyTorch Week 3 -- container of nn.Module: Sequential, ModuleList, ModuleDice PyTorch Week 3 - model creation PyTorch Week 2 - Dataloader and Dataset PyTorch Week 1 preface In this section, the principle of gradie ...

t o r c n . n n \qquad torcn.nn torcn.nn is a modular interface specially desi ...

The previous article explained the logistic regression model of deep learning. This article will next talk about the vectorization of logistic regression and the basic code required for compilation.   1.sigmoid function:                                                       The sigmoid function can be compiled using python's math libraryH ...

1 data set introduction ShpaeNet is a common data set in the point cloud. It can complete the task of component segmentation, that is, the component knows the segmentation of large data in the point cloud, and also needs to segment its widgets. It includes a total of 16 categories, each of which can be divided into several sub categories (for ...

What do I knowMy WeChat official accountMy CSDNDownload this article source code + dataNeed help. Ctrl+D: favorite this page In this tutorial, you will learn how to use migration learning to classify images of cats and dogs through a pre training network. The pre training model is a saved network previously trained based on large data sets ...

MMdetection official Chinese document 1: reasoning on standard data sets using existing models MMDetection in Model Zoo It provides hundreds of detection models and supports a variety of standard data sets, including Pascal, VOC, COCO, Cityscapes, LVIS, etc. This document will describe how to use these models and standard data sets to run some ...

Learning Summary (1) Each optimizer is a class and must be instantiated before it can be used, for example: class Net(nn.Moddule): ··· net = Net() optim = torch.optim.SGD(net.parameters(), lr=lr) optim.step() (2) optimizer implements the following two steps in epoch of a neural network: Gradient zero, gradient update. optimizer = torch ...

BILSTM-CRF code Code from Named entity recognition (NER): introduction to the principle of BiLSTM-CRF + pytoch_ Tutorial code parsing Part I: Guide Package 1.torch.nn package mainly contains Modules used to build each layer, such as full connection, two-dimensional convolution, pooling, etc; The torch.nn package also contains a series of usefu ...